Optimization is a technique of controlling a process, so as to optimize a specified set of parameters without violating constraints of the process. Known optimization processes in a power plant are carried out to increase efficiency, lower possible emissions, reduce cost, and maximize system availability for power generation. There are several systems that may be optimized independently in the power plant for better performance. For example, upgrading a specific component of equipment in the power plant can result in less fuel consumption. Also, the overall operation of the power plant may be optimized, by optimizing one or more factors that contribute to overall efficiency of the power plant.
It is known to optimize load scheduling in the power plant to minimize operational cost, and known techniques exist for optimizing load scheduling. For example, load scheduling may be optimized based on a load demand (e.g., the power plants are scheduled in such a manner that the load demand is met). As another example, load scheduling may also be optimized to meet a predetermined maintenance schedule.
As one can easily see, the operation of load scheduling can have cost implications and the cost associated with load scheduling can be referred as “cost of load scheduling”. The cost of load scheduling may be determined from the capital cost of the equipment, fuel cost, cost of chemicals, cost of spare equipment and parts, and maintenance cost. Apart from the capital cost and the fuel cost, the maintenance cost can be considered a significant expenditure for a power plant and a shift in the maintenance schedule may have significant change in the cost of load scheduling.
The maintenance schedule of equipment may be based on regular intervals, elapsed time, or run-time meter readings. Therefore, it is often desired to adapt to any unforeseen shift or preplanned shift in the maintenance schedule to minimize the cost. Moreover, overall operation cost of the power plant also can change due to the shift in the maintenance schedule. A maintenance schedule is based on downtime resulting from scheduled maintenance of power plant components and unplanned or forced shutdowns because of sudden failure and repair activity. It can be desirable to have planned and scheduled maintenance and avoid the unplanned maintenance. Therefore, maintenance activities are scheduled periodically and as frequent as possible either as recommended by the manufacturer or based on the operator's past experience.
Delaying the planned maintenance schedule may increase the unplanned maintenance and the associated cost. Advancement of the maintenance schedule may influence unnecessary maintenance activities and the maintenance costs. It is to be noted that there are multiple scheduling tools for scheduling production as well as maintenance but, this is often not based on the actual operating conditions and state of the component or operation under consideration.
The maintenance actions for the power plant components can be notified by corresponding maintenance triggers in the form of an electronic representation which are the inputs for such scheduling tools. As per the maintenance triggers, these tools will find the schedule for maintenance actions along with the production scheduling for the period of time. In such scheduling approaches, the optimization techniques used are, for example, only based on cost consideration and do not include actual operating conditions and state of the components.
With advent of advanced control systems and with increased computational power available with such control systems, more features are being included for optimization. In a control system, optimization may be carried out with an optimization module or a component that is already integrated with the control system or may be carried out separately based on the information available from the plant. However, it is common to find the former means (e.g., having the optimization module already embedded in the control system). In many cases, the optimization module utilizes a statistical or physics based model approach (first principle model) for evaluation of optimal settings. Other approaches such as that based on neural network or syntactic may also be practiced.
In case of load scheduling operation, the optimized output values are the various set points to the controllers controlling the plant. The provided set points are such that the plant in an overall sense functions to meet specifications (e.g., load demand, operation cost, efficiency, safety and regulatory specifications, maintenance specifications, etc.).
As already mentioned, in many cases, optimization is based on statistical or a first principle model based approach. In such approaches, essentially there is at least one mathematical expression that relates a property of the plant as a function of measured or estimated parameters of the plant. Some examples of a property of the plant are generator power output, boiler steam generation, fuel utilization, maintenance schedule, age or life expectancy of a particular unit in the plant, etc. The mathematical models used can be related to performance of individual units in the plant or for overall coordinated functioning of the plant. In many cases, performance includes cost functions or these may be derived by suitable formulation of an optimization problem.
On a specific aspect of load scheduling and influence of maintenance activity, one skilled in the art would recognize that it is common to find a predefined schedule prescribed for maintenance, though in practice maintenance activity may be an unforeseen activity carried out as a result of failure of one or several components in a power plant. As the cost of a power plant being unable for service is very high, the design of a power plant is made having sufficient redundancy and margins to withstand unusual loads or scenarios. In addition, there is adequate general knowledge or history present with the power plants about maintenance or service activities for the plant that one skilled in the art would recognize what kind of load or scenario is likely to cause failure of what component, and the associated cost and downtime as a consequence of the maintenance activity. This knowledge can be efficiently utilized for scheduling the load for the power plant and include a schedule for maintenance activity considering the state of the plant.
In light of the foregoing discussion, exemplary embodiments disclosed herein are directed to an efficient technique for scheduling the load for a power plant, and developing an optimization module present in the control system to take care of maintenance scheduling.